Massive Multitask Language Understanding Leaderboard
Tests broad knowledge across 57 academic subjects (STEM, humanities, social sciences) with 16,000 multiple-choice questions. The most widely-cited LLM benchmark.
Why it matters: Shows how well a model has absorbed factual knowledge during training. Saturating above 90%, so less useful for differentiating frontier models.
Top Model
94%
GPT-5.4
Average Score
87.9%
Across 52 models
Models Tested
52
Metric: accuracy
Human Baseline
89.8%
Score Range: 0%–100%
MMLU Scores - Top 25 Models
Ranked by MMLU score (%)
Model Rankings
All models with a reported MMLU score, ranked by highest accuracy.
About MMLU
- Full Name
- Massive Multitask Language Understanding
- Category
- Knowledge
- Metric
- accuracy (%)
- Score Range
- 0%–100%
- Human Baseline
- 89.8%
- Status
- Saturated
MMLU is a standardized evaluation that measures AI model performance on specific tasks. It provides comparable scores across different models, helping developers choose the right model for their needs.
GPT-5.4 currently holds the top score on the MMLU benchmark. See our full rankings table above for the complete leaderboard with 52 models.
We update benchmark data from multiple sources including HuggingFace open-source model leaderboards and LMArena. Scores are refreshed regularly as new evaluations are published and new models are released.
No. While MMLU is an important indicator, real-world performance depends on many factors including pricing, latency, context window, and specific task requirements. We recommend using our composite score which weighs multiple benchmarks and practical factors.